/*=========================================================================
 *
 *  Copyright NumFOCUS
 *
 *  Licensed under the Apache License, Version 2.0 (the "License");
 *  you may not use this file except in compliance with the License.
 *  You may obtain a copy of the License at
 *
 *         https://www.apache.org/licenses/LICENSE-2.0.txt
 *
 *  Unless required by applicable law or agreed to in writing, software
 *  distributed under the License is distributed on an "AS IS" BASIS,
 *  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 *  See the License for the specific language governing permissions and
 *  limitations under the License.
 *
 *=========================================================================*/


#include "itkCovarianceImageFunction.h"
#include "itkImageFunction.h"
#include "itkTestingMacros.h"

int
itkCovarianceImageFunctionTest(int, char *[])
{
  constexpr unsigned int Dimension{ 3 };
  using PixelComponentType = unsigned char;
  constexpr unsigned int VectorDimension{ 4 };

  using PixelType = itk::FixedArray<PixelComponentType, VectorDimension>;
  using ImageType = itk::Image<PixelType, Dimension>;
  using FunctionType = itk::CovarianceImageFunction<ImageType>;

  // Create and allocate the image
  auto                          image = ImageType::New();
  constexpr ImageType::SizeType size{ 20, 20, 20 };
  ImageType::RegionType         region = { size };

  image->SetRegions(region);
  image->Allocate();

  ImageType::PixelType initialValue{ { 11, 13, 17, 19 } };
  image->FillBuffer(initialValue);

  auto function = FunctionType::New();
  ITK_EXERCISE_BASIC_OBJECT_METHODS(function, CovarianceImageFunction, ImageFunction);

  function->SetInputImage(image);

  constexpr unsigned int neighborhoodRadius{ 5 };
  function->SetNeighborhoodRadius(neighborhoodRadius);
  ITK_TEST_SET_GET_VALUE(neighborhoodRadius, function->GetNeighborhoodRadius());

  constexpr ImageType::IndexType index{ 10, 10, 10 };

  FunctionType::OutputType covariance = function->EvaluateAtIndex(index);
  std::cout << "function->EvaluateAtIndex( index ): " << covariance << std::endl;

  // Test Evaluate
  FunctionType::PointType        point{ { 25, 25, 25 } };
  const FunctionType::OutputType covariance2 = function->Evaluate(point);
  std::cout << "function->Evaluate(point): " << covariance2 << std::endl;

  // Test EvaluateAtContinuousIndex
  FunctionType::ContinuousIndexType cindex{ { 25, 25, 25 } };
  const FunctionType::OutputType    covariance3 = function->EvaluateAtContinuousIndex(cindex);
  std::cout << "function->EvaluateAtContinuousIndex(cindex): " << covariance3 << std::endl;

  constexpr ImageType::IndexValueType imageValue{ 0 };
  // Since the input image is constant, the covariance should be equal to
  // the initial value
  for (unsigned int ix = 0; ix < VectorDimension; ++ix)
  {
    for (unsigned int iy = 0; iy < VectorDimension; ++iy)
    {
      // Covariance must be zero in this image with constant values
      if (!itk::Math::FloatAlmostEqual(itk::Math::abs(covariance[ix][iy]),
                                       static_cast<FunctionType::OutputType::element_type>(imageValue),
                                       10,
                                       10e-7))
      {
        std::cerr << "Error in covariance computation" << std::endl;
        return EXIT_FAILURE;
      }
    }
  }

  std::cout << "Test PASSED ! " << std::endl;
  return EXIT_SUCCESS;
}
